Course description
Computing in Python IV: Objects & Algorithms
Complete your introductory knowledge of computer science with this final course on objects and algorithms. Now that you've learned about complex control structures and data structures, learn to develop programs that more intuitively leverage your natural understanding of problems through object-oriented programming. Then, learn to analyze the complexity and efficiency of these programs through algorithms. In addition, certify your broader knowledge of Introduction to Computing with a comprehensive exam.
By the end of this course, you'll be able to write programs in Python that leverage your more natural understanding of data structures by creating objects to represent the structures you work with most often. For example, if you were creating a class roster application, you'll learn how to create an object representing a student's name, ID number, and attendance record. Then, you'll be able to create applications that leverage sorting and searching algorithms to sort that roster alphabetically, search for a particular student, and evaluate the efficiency of both those operations.
Upcoming start dates
Suitability - Who should attend?
Prerequisites
CS1301xIII or equivalent knowledge is required. Certain problems may benefit from experience with algebra, geometry, pre-calculus, and trigonometry, but you can succeed without these.
Outcome / Qualification etc.
What you'll learn
- Working with instances of objects in Python.
- Creating new data structures using object-oriented programming.
- Using objects with earlier control and data structures.
- Writing common search algorithms, like linear and binary search.
- Writing common sorting algorithms, like bubble sort, insertion sort, and merge sort.
- Evaluating the computational complexity of algorithms using Big O notation.
Training Course Content
Chapter 1. Objects. Working with instances of complex data types or defining your own, like creating a class to represent a video game character, a class syllabus, or an item for sale.
Chapter 2. Algorithms. Creating complex code for searching in large lists or sorting lists of data, and analyzing code for its complexity.
Chapter 3. Course Recap. A comprehensive review of the Xseries as a whole, leading into the final exam.
Course delivery details
This course is offered through The Georgia Institute of Technology, a partner institute of EdX.
9-10 hours per week
Expenses
- Verified Track -$149
- Audit Track - Free